A number of communication networks and systems, such as, but not limited to high data rate optical communication systems, employ communication channels that are dispersive—in that they cause the energy of a respective signal component to be dispersed or spread in time as it is transported over the channel. In an effort to reduce the effects of dispersion, some systems predistort the signal in a manner that is intended to be ‘complementary’ to the effect of the channel, so that ‘optimally’ at the receiver the original signal, prior to the predistortion operation, may be recovered. Other systems attempt to ameliorate the problem by dealing directly with the channel itself, such as by using dispersion compensating fibers (DCFs). These approaches can be difficult or expensive to apply and, from a functional and architectural standpoint, are relatively rigid, so that they tend to be easily impacted by operational or environmental changes, such as mechanical vibration or variations in temperature.
Other approaches attempt to solve the problem at the receiver, such as through the use of some form of equalizer, which is operative to estimate the inverse effect of the channel on the signal, so that, ideally, the output of the equalizer is the original signal without the dispersive influence of the channel. Because the channels are subject to dynamic variation, the equalizer should be adaptive and, for this purpose, it is customary to initially train the equalizer prior to data transmission and then occasionally adjust the equalizer at prescribed intervals with a training sequence dedicated for the purpose. While this technique is effective at adapting the equalizer's coefficients and reducing channel-induced dispersion, it requires dedicated ‘training sequence’ communications between the transmitter and receiver, which inherently interrupts the transmission of user data, thereby reducing the effective user data rate.